Grain noise reduction using the human visual system characteristics

This paper deals with grain noise artifact reduction on archived films. Concretely, our research has been focused on finding a technique that let us not only reduce the grain noise but also preserve the original image quality as accurate as possible. The paper investigates the influence of different types of noise reduction filters in order to introduce the problem. Moreover, for each technique some conclusions are exposed. Finally, a linear spatial-temporal technique is proposed and described. This technique adapts a spatial-temporal response according to the human visual system behavior. Taking advantage of it, we get great results reducing the grain noise of several image sequences and preserving their original quality as much as possible. Moreover, the filter does not need motion estimation and it is implemented using separable filters, resulting a computational efficient implementation.